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All Journal JURNAL INFORMATIKA Conference on Innovation and Application of Science and Technology (CIASTECH) JSI (Jurnal sistem Informasi) Universitas Suryadarma Scientific Journal of Informatics G-Tech : Jurnal Teknologi Terapan Community Development Journal: Jurnal Pengabdian Masyarakat GANDRUNG: Jurnal Pengabdian Kepada Masyarakat Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Journal of Students‘ Research in Computer Science (JSRCS) As-Sidanah : Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Al-Khidmah Jurnal Pengabdian Masyarakat JUSTIFY : Jurnal Sistem Informasi Ibrahimy Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS JEECS (Journal of Electrical Engineering and Computer Sciences) Journal Of Computer Science And Technology JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Jurnal Ilmiah Multidisiplin Nusantara Jurnal Cendekia Mengabdi Berinovasi dan Berkarya Jurnal Pengabdian Sosial GEMBIRA (Pengabdian Kepada Masyarakat) NGARSA: Journal of Dedication Based on Local Wisdom JUAN: Jurnal Pengabdian Nusantara Jurnal Riset Teknik Komputer Jurnal Pengabdian Masyarakat Ekonomi dan Bisnis Digital Jurnal Padamu Negeri Jurnal Sistem Informasi Karya Anak Bangsa Journal Educational Research and Development Journal Dekstop Application (JDA) Jurnal Teras Pengabdian Masyarakat (JISCO) Journal of Information System and Computing NJCOM: Community Service Journal Jurnal Pengabdian Masyarakat Multidisiplin Journal Of Global Computer Science
Fatah, Zaehol
Fakultas Sains Dan Teknologi Universitas Ibrahimy
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Physics Public Health Social Sciences Other

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PELATIHAN DESAIN GRAFIS MENGGUNAKAN ADOBE PHOTOSHOP BAGI SISWA SMP NEGERI 1 JANGKAR Siti Farhatus Shofiyyah; Zaehol Fatah
Jurnal Padamu Negeri Vol. 3 No. 3 (2026): Juli : Jurnal Padamu Negeri (JPN)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/hm4crq07

Abstract

The development of digital technology requires students to possess adequate digital literacy and creativity skills. This study aims to describe the implementation of graphic design training using Adobe Photoshop, analyze the improvement of students’ digital skills and creativity, and identify students’ responses to the program. The research employed a descriptive approach involving 32 students of SMP Negeri 1 Jangkar. Data were collected through observation, questionnaires, documentation, and performance assessment. The results showed that student attendance reached 95%, active participation was 88%, and task completion was 84%. The average score increased from 58 in the pre-test to 84 in the post-test, with a mastery level of 84%. Most students responded positively to the training. The findings indicate that practice-based training using Adobe Photoshop is effective in improving students’ graphic design skills, creativity, and digital literacy.
PEMANFAATAN FITUR TEMPLATE PADA CANVA UNTUK MENINGKATKAN EFISIENSI DAN KREATIVITAS SISWA DI SMP 3 IBRAHIMY Zaehol Fatah; Ummariyatul Fitriyah
Jurnal Padamu Negeri Vol. 3 No. 3 (2026): Juli : Jurnal Padamu Negeri (JPN)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/2sdxyg11

Abstract

This study aims to examine the impact of using Canva templates on students' work efficiency and creativity. Canva is a web-based platform that provides a wide range of ready-to-use design templates to support teaching and learningactivities. Previous studies have shown that Canva is an effective learning medium that enhances students' engagement, creativity, and productivity. Thisstudy employed a literature review method to analyze findings from relevant scientific publications. The results indicate that Canva's template features helpstudents complete their tasks more efficiently, foster creativity, and create a more engaging and interactive learning environment. Therefore, the use of Canva templates can serve as an effective alternative learning medium to improve the quality of teaching and learning at SMP 3 Ibrahimy.      
Implementasi Metode Decission Tree Dalam Mengklasifikasi Depresi Menggunakan Rapidminer Syariful Abrori; Zaehol Fatah
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/vgf7xb32

Abstract

Depression has become a serious mental health problem with a significant impact on quality of life and work productivity. This study aims to develop a depression classification model using the Decision Tree method implemented through RapidMiner software. The dataset consists of 2054 data with 11 variables covering demographic aspects, working conditions, and mental health. Data preprocessing is carried out through several stages, including data format conversion, categorical variable transformation using Nominal to Binominal, and numeric data normalization with Z-transformation. Implementing the Decision Tree uses the gain ratio parameter as the criterion, maximum depth 10, and confidence 0.1, and activates the pruning and prepruning features for model optimization. The results showed excellent performance with an accuracy of 97.50%, a weighted mean recall of 92.29%, and a weighted mean precision of 93.49%. The confusion matrix shows that the model successfully identified 1463 non-depression cases and 139 depression cases correctly, with a low misclassification rate.
Klasifikasi Berita Hoaks Di Media Sosial Menggunakan Algoritma Naive Bayes dan RapidMiner Ummul Karimah; Zaehol Fatah
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.4028

Abstract

The development of information technology and social media has made the distribution of information easier, but it has also increased the prevalence of fake news or hoaxes. This research aims to classify hoax and non-hoax news on social media using the Naïve Bayes algorithm with the assistance of the RapidMiner application. The data used is secondary data obtained from the Kaggle website and processed thru text preprocessing stages including tokenization, stopword removal, stemming, and TF-IDF weighting. The classification process was carried out using the Cross Validation method to measure model performance. The research results show that the Naïve Bayes algorithm has an accuracy of 90.20%, and precision values of 92.25% for the hoax class and 88.33% for the non-hoax class, with recall values of 87.78% and 92.62% respectively. These values indicate that the built classification model can easily identify hoax news. Thus, the Naïve Bayes algorithm has proven to be effective and efficient for use as a method for detecting fake news on social media. Keywords: Naïve Bayes, RapidMiner, Classification, Hoax News, Text Mining
Prediksi Resiko Penyakit Menggunakan Algoritma Random Forest sebagai Upaya Pencegahan Kesehatan Masyarakat Alvina Jelita Firdaus; Zaehol Fatah
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.4029

Abstract

Chronic diseases influenced by lifestyle factors are a crucial public health issue, while predictive models are often limited by class imbalance and a lack of clinical interpretability. This research aims to build an accurate and transparent disease risk prediction model based on lifestyle factors. The method used is hybrid classification, combining the Random Forest algorithm with the SMOTE (Synthetic Minority Oversampling Technique) technique to effectively address the initial data imbalance (3:1 ratio) in the Health Lifestyle Dataset. This balanced data was then split 80:20 for testing. The test results show the model achieved an aggregate accuracy of 74.43%, with strong precision (79%) for the risk class, indicating prediction reliability. Feature Importance analysis provides significant clinical insights, identifying Daily Water Intake (water_intake_l) and Sleep Duration (sleep_hours) as the most dominant predictive factors, even surpassing physiological factors. The conclusion indicates that this hybrid approach is effective as an early screening instrument, with the main advantage being the transparency of lifestyle variable interpretation, which directly supports data-driven prevention strategies
Penerapan Algoritma Decision Tree untuk Klasifikasi Kelulusan Mahasiswa Berdasarkan Faktor Akademik dan Sosial Dofiyanto; Zaehol Fatah
JISCO : Journal of Information System and Computing Vol 3 No 2 (2025): Jurnal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v3i2.4030

Abstract

This research aims to employ the C4.5 Decision Tree technique to classify the results of student graduation. This is achieved by taking into account both their scholastic performance and social factors. Scholastic performance indicators encompass the student's overall grade average, their academic status, and how often they attend classes, whereas social factors include their age, whether they are married, and their engagement in extracurricular activities. The information utilized was taken from an internal compilation of student information, which was refined and modified with the RapidMiner program. To ensure the correctness of the predictions, the categorization model was confirmed through the implementation of a 10-fold cross-validation strategy. The results of the tests demonstrated an 89.44% level of correctness, as well as a 91.38% level of precision and a 90.28% rate of recall, showing that the model functions at a level that is both remarkably successful and reliable. These discoveries reinforce the idea that the C4.5 Decision Tree algorithm is capable of accurately determining the patterns in student graduation through the integration of both scholastic and social elements. This can then act as a foundation for making scholastic decisions to improve the efficiency of the process of higher education.
Classification of Diabetes Patients Using Decision Tree Algorithm with RapidMiner Agel Ahmad Maulana; Zaehol Fatah
JISCO : Journal of Information System and Computing Vol 4 No 1 (2026): Journal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v4i1.4032

Abstract

Diabetes melitus merupakan penyakit tidak menular dengan tingkat prevalensi yang terus meningkat, sehingga memerlukan metode deteksi dini yang efektif. Penelitian ini bertujuan untuk mengimplementasikan algoritma Decision Tree dalam mengklasifikasikan pasien diabetes berdasarkan parameter medis seperti kadar glukosa, tekanan darah, insulin, BMI, dan usia. Data yang digunakan bersumber dari dataset diabetes Kaggle yang mencakup 768 catatan kesehatan. Metodologi penelitian meliputi tahap transformasi data, pemodelan menggunakan RapidMiner, dan evaluasi model. Hasil penelitian menunjukkan bahwa algoritma Decision Tree mampu membentuk model klasifikasi yang akurat dengan atribut glukosa sebagai faktor prediktor paling dominan. Model ini memberikan visualisasi aturan keputusan yang intuitif, sehingga dapat dijadikan landasan bagi pengembangan sistem pendukung keputusan untuk deteksi dini diabetes di lingkungan klinis.
Identifikasi Pola Penyebaran Penyakit Ternak Menggunakan Clustering Spasial Zainal Mu'en; Zaehol Fatah
Journal Of Global Computer Science Vol. 1 No. 1 (2025): JGCS - FEBRUARY
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jgcs.v1i1.2025.23

Abstract

Penyakit hewan merupakan salah satu tantangan terbesar dalam divisi hewan yang dapat mengakibatkan kerugian finansial yang signifikan. Bukti yang dapat dikenali dari pola penyebaran penyakit sangat penting untuk mendukung pengambilan keputusan dalam upaya mengantisipasi dan menangani wabah . Pertimbangan ini bertujuan untuk menganalisis dan mengidentifikasi pola penyebaran penyakit hewan menggunakan strategi pengelompokan spasial . Strategi ini memungkinkan pengelompokan wilayah berdasarkan tingkat penyebaran penyakit , sehingga zona yang berpotensi menjadi pusat penyebaran dapat diidentifikasi . Informasi yang digunakan dalam pertimbangan ini mencakup data spasial dan non - spasial yang terkait dengan kasus penyakit hewan dari berbagai wilayah , yang kemudian dianalisis di sana. Hasil dari penelitian ini menunjukkan bahwa strategi pengelompokan spasial dapat diterapkan di daerah -daerah dengan pola penyebaran penyakit yang sama . Identifikasi zona berisiko tinggi dapat membantu peternak dan pihak terkait dalam mengambil tindakan penanggulangan yang lebih tepat dan efisien . Dengan pengelompokan spasial ini , prosedur penanganan dapat difokuskan pada daerah-daerah yang lebih rentan terhadap kejadian , yang diharapkan dapat mengurangi dampak ekonomi dan meningkatkan kesejahteraan hewan secara keseluruhan . Penelitian ini memberikan kontribusi penting bagi pengembangan kerangka kerja deteksi dini berbasis teknologi untuk mitigasi penyakit ternak
Implementasi K-Means Clustring Untuk Mengelompokkan Provinsi di Indonesia Berdasarkan Tingkat Pengangguran Terbuka Muhammad Muhajir Saddami; Zaehol Fatah
Journal Of Global Computer Science Vol. 1 No. 1 (2025): JGCS - FEBRUARY
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jgcs.v1i1.2025.24

Abstract

Pengangguran terbuka di Indonesia merupakan salah satu masalah sosial dan ekonomi yang signifikan, yang dapat menghambat pertumbuhan ekonomi serta mempengaruhi kesejahteraan masyarakat secara luas. Penelitian ini bertujuan untuk menganalisis Tingkat Pengangguran Terbuka (TPT) Indonesia dari tahun 2020 hingga 2023, dengan fokus pada perubahan klaster data TPT menggunakan metode K-Means Clustering. Data yang digunakan diambil dari Badan Pusat Statistik (BPS), yang memberikan gambaran komprehensif mengenai variasi TPT antarprovinsi. Metodologi yang diterapkan mencakup pengumpulan dan pengolahan data untuk memastikan akurasi serta kelengkapan informasi. Hasil analisis menunjukkan bahwa hanya Provinsi Riau yang berhasil naik ke cluster 1 (TPT rendah), sementara Provinsi Sumatera Barat mengalami penurunan ke cluster 2 (TPT tinggi). Evaluasi menggunakan Davies-Bouldin Index menegaskan pemisahan cluster yang optimal pada jumlah cluster 2, mengindikasikan efektivitas pengelompokan. Temuan dari penelitian ini diharapkan dapat memberikan wawasan berharga bagi pembuat kebijakan untuk merumuskan strategi yang lebih efektif dalam mengatasi masalah pengangguran di Indonesia. Dengan mempertimbangkan karakteristik pengangguran di setiap provinsi, hasil penelitian ini dapat menjadi dasar bagi upaya pengurangan tingkat pengangguran yang lebih terarah dan berdampak.
Pelatihan Penulisan Makalah Menggunakan Aplikasi Microsoft Word Di MA Nurul Huda Mereng Pemalang Syafiq Ilham Hakim; Muhammad Nabil Dhiya’ul Haq; Zaehol Fatah
Jurnal Cendekia Mengabdi Berinovasi dan Berkarya Vol 4 No 1 (2026): Oktober 2025 - Januari 2026
Publisher : Universitas Madako Tolitoli

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56630/jenaka.v4i1.1046

Abstract

Kegiatan pelatihan penulisan makalah menggunakan program aplikasi Microsoft Word ini merupakan bagian dari program pengabdian kepada masyarakat yang bertujuan untuk mengembangkan kemampuan literasi digital dan keterampilan akademik siswa MA Nurul Huda Mereng di Pemalang. Masalah yang dihadapi adalah kurangnya pemahaman siswa dalam menyusun karya ilmiah secara sistematis. Pelatihan diikuti oleh 22 peserta. Metode pelaksanaan menggabungkan penjelasan konsep secara teoritis dengan praktik langsung melalui pendekatan partisipatif. Hasil kegiatan menunjukkan bahwa siswa mengalami peningkatan pemahaman dalam menyusun makalah sesuai kaidah ilmiah, seperti pembuatan halaman sampul, struktur isi, penomoran halaman, dan referensi. Kesimpulannya, program ini terbukti efektif dalam membantu siswa mempersiapkan diri menghadapi tuntutan penyusunan karya ilmiah di tingkat madrasah maupun jenjang pendidikan lebih lanjut, serta menumbuhkan minat terhadap pemanfaatan teknologi dalam proses pembelajaran.
Co-Authors Abd. Moeqshit Abdul Jalil Abu Dzarrin Al Ghifari Achmad Baijuri Achmad Nanung Fambriyadi Adinia Zulfa nurany Afdhaliyah Ramadhatul Fitriyah Agel Ahmad Maulana Agus Hamid Cholil Ahmad Afif Azmi Ahmad Efendi Ahmad Farissul Haq Ahmad Fauzan Ahmad Homaidi Ahmad Muflih Wafir Ahmad Wahyu Fernando Ahmad Yasin Ahmad Yogianto Ahmada Ilham Huzaini Ainur Yakin Aisyah Putri Sabrina Akhlis Munazilin Ali Muhajir Alifan Ibrohim Alvananta Farhan Maulana Alvina Jelita Firdaus Angga Saputra Anis Mukarromah Anisatul Rhodiah Ardila Dwi Putri Asvic Baid Anbala As’ad Alwi Shihab Auliya Auliya Bayu Ainur Rifki Cindy Nur Dina Alifia Daniel As’ad Amrullah dewi khoirunisak Dhiyaul Haq Hasan Dofiyanto Dwi Inayatul Fadila Dwi Norrepa Egi Gusnandi Pratama Endah Wahyu Rizki Eny Itsnainy Agustin Evvatun Nafiah Faqih Nur Rahman Farizal Maulana Sopyan Fikri Febrian Filsa Salsabila Fitra Lia Shofiah Hilma Aufini Ika Ayu Herlina Imam Nawawi Indra Hidayatullah Sofyan Intan Nayla Widad Hidayat Iqbal Saputra Irma Siftiana Irma Yunita Irma Yunita Jarot Dwi Prasetyo Jarot Dwi Prasetyo Karomah Nikmatul Maula Khoiriyah Agustin Ulumiyah Kiki Setiawan Heri Ananda Putra Lailatul Badriya Lailatur Romadhaniyah Lisa Muhfidha Lukman Aliyasin Lukman Fakih Lidimilah Lummatul Aisi aisi M. Fazlur Rahman Assauqi Madatahliya Mahattir Rahman Muhammad Mahmudi Mahmudi Manisa Sopia Mori mori Maridatul Husna Mas’udah masudah Maulidya Hanun Mayla Dini Zakkia Mita Abelia Moh Nailul Fahmi Moh. Aqil Mukhtar Alfarera Moh. Bahauddin Mohamad Afil Nadiq Nabil Mohammad Hadi Sujatmiko Mohammad Zainuddin Muhamad Iqbal Facruzi Muhammad Al Madany Muhammad Ilzam Asrori Muhammad Irsyad Syarif Muhammad Marizal Muhammad Muhajir Saddami Muhammad Nabil Dhiya’ul Haq Muhammad Nur Alif Haqiqi Muhammad Salman Al Farisy Muhammad Syafiq Muhammad Zakaria Muwasatil Muhtajin Nafilil Madani Al-Qur’ani Naila Ismi Fadila Nasywa Faiz Atillah Mifta Nauradhia Shofarianti Putri Nazwa Andita Neny Yuli Susanti Neny Yuli Susanti Nori Nur Fasratul Aini Nur Aini Nur Azizah Nur Kamila Nurul Lailiyah Putri Ghina Ardhika Putri Ilma Raudatuss Syifa Putri Navizah Qurrotul A'yun Rafi Jaabil Haqqi Rahmat Syarifuddin Chairil Anwar Rendi Aldiansyah Resti Aprilianingsih Riana Agustin Rifki Dwi Saputra Rinayatul Fadilah Riskiyatul Hasanah Risma Nur Kholishah Rofi Dian Andini Rofiatul Aulia Rohiqim Mahtum Rohiqim Mahtum Roy Hamdan Samsul Shinta Nuriyah Lailatul Iqrimah Siti Afiyah Suryadi Rahmah Siti Farhatus Shofiyyah Sitti Hafidzaturrafiah Sofiatuz Zamani Sri Wahyuni Supandi Syadza Najwatis Shaleha Syafiq Ilham Hakim Syamsul Arifin Syarif Hidayatullah Syariful Abrori Taufik Saleh Taufik Saleh Tawakal, Anzori Tilawatus Syarqiyah Tuti Alawiyah Ubay Dillah Mas’ud Ulfatun Najiyah Ummariyatul Fitriyah Ummul Karimah Uny Khafifah Uswatul Muftakiyah Wahyu Achmad Putra wardatun nafisa wardhatun khasanah Yaumil Farah Zainal Mu'en Zainul Arifin Alwi Al Qayyis Zainur Rohman Zeinurrahman Zeinurrahman